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P-93 Relationship between global positioning system derived measures and heart rate variability after two weeks of training in professional soccer
  1. Anil Isik1,
  2. Turgay Aslanyrek1,
  3. mer Batin Gzbyk2,
  4. Bernard Tahirbegolli1
  1. 1Acibadem Sports FIFA Medical Center of Excellence, Turkey
  2. 2Sports Medicine Department, Istanbul University, Istanbul Faculty of Medicine, Turkey

Abstract

In spite of demonstrating training loads objectively through player tracking system and Global Positioning System (GPS) technologies, a precise and reliable monitoring tool which can detect the risk of non-functional overreaching or overtraining has not yet been found. Although many methods and tools used until today, it is very difficult to monitor overtraining risk which is a multifactorial physiological process with serious individual differences. Today seasonal periodization strategies can be planned with the help of player tracking technologies which can determine internal and external training load, but it still remains a question mark if the athletes can show optimal physiological adaptation to these applications.

In this study, we monitored the external training load parameters including total distance, high speed running distance, explosive distance and sprint number; and HRV which has been shown with some studies to be one of the early determinants of overtraining.

Data collected from 22 elite soccer players from Turkish national team is used for this study. Turkish Football Federation gave consent with document number 2016–2017/001 for the data to be used in this study. 18 out of 22 GPS recordings were eligible for further analysis. GPS measures recorded in every training were; total distance (TD) covered, high speed running (HSR) distance, explosive running (ER) distance and number of sprints (SP). Heart rate variability of the players was recorded using a commercially available smartphone device, ithlete, 3 times during a 14 days training camp. HRV changing trend was analyzed with one-way ANOVA, and correlation between GPS-derived measures and HRV scores were analyzed with Pearson test. Wilcoxon test was used in order to detect any statistically significant difference between repeated measures. Statistical analysis was performed with SPSS version 21 and p ≥ 0.05 was accepted as level of significance.

There was a statistically significant increase in total distance between day 1 and day 14 (p ≥ 0.05). A decreasing trend has been detected in HRV scores although the change was not significant (F = 0.948; p = 0.335). There was a low positive correlation between mean measures of TD, and low negative correlation between that of HSR and SP and heart rate variability scores (r = 0.312, r = −0.353, r = −0.461 respectively).

An increasing total distance towards the end of the camp was the periodization strategy of the team and has been shown statistically in this study. Based on studies about HRV, moderate decreases in HRV were considered as a signal of functional overreaching, significant decreases were considered as a signal of non-functional overreaching and overtraining, while increases in HRV were considered as a signal of recovery. In short and intense period of this preparation camp, HRV responses of athletes was expected to show a decreasing trend. TD was monitored as an indicator of training volume, HSR, ED and SP were monitored as indicators of training intensity.

HSR and SP, considered to reflect training intensity showed low negative correlation, and TD, reflecting training volume showed low positive correlation with HRV scores. Low negative correlation between HRV and HSR and SP was interpreted as negative physiological adaptation after high intensity / low volume training load. Low positive correlation between HRV and TD was interpreted as positive physiological adaptation after low intensity / high volume training load. Therefore, HRV might be used to monitor physiological responses of athletes to external training load during short term and intense training periods however larger longitudinal studies are needed for HRV to be used solely as an early signal of overtraining.

In order to detect early signals of overtraining and prevention, future studies must focus on the data obtained by more frequent and regular (daily) measurements of the parameters which are considered as training load and overtraining indicators.

Abstract P-93 Figure 1
Abstract P-93 Figure 1

Mean of total distance covered and heart rate variability of 18 elite soccer players

TD: total distance covered on meters; HRV: heart rate variability

References

  1. Andrew AF, Micheal RE. Validity of the ithlete Smart Phone Application for Determining Ultra-Short-Term Heart Rate Variability. J Hum Kinet 2013;(39):85–92.

  2. Mourot L, Bouhaddi M, Perrey S, Cappelle S, Henriet MT, Wolf JP, Rouillon JD, Regnard J. Decrease in heart rate variability with overtraining: assessment by the Poincar plot analysis. Clin Physiol Funct Imaging 2004 Jan;24(1):10–8.

  3. Ritchie D, Hopkins WG, Buchheit M, Cordy J, Bartlett JD. Quantification of Training and Competition Load Across a Season in an Elite Australian Football Club. Int J Sports Physiol Perform 2016 May;11(4):474–9.

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